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Record W4399042750 · doi:10.3390/pharmaceutics16060719

Current Progress in Magnetic Resonance-Guided Focused Ultrasound to Facilitate Drug Delivery across the Blood-Brain Barrier

2024· article· en· W4399042750 on OpenAlexaff
Ying Meng, Lorraine V. Kalia, Suneil K. Kalia, Clement Hamani, Yuexi Huang, Kullervo Hynynen, Nir Lipsman, Benjamin Davidson

Bibliographic record

VenuePharmaceutics · 2024
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsUniversity Health NetworkUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineFocused ultrasoundDrug deliveryClinical trialBlood–brain barrierMagnetic resonance imagingDrug delivery to the brainDrugUltrasoundDiseaseTargeted drug deliveryPharmacologyCentral nervous systemPathologyInternal medicineRadiologyNanotechnology

Abstract

fetched live from OpenAlex

This review discusses the current progress in the clinical use of magnetic resonance-guided focused ultrasound (MRgFUS) and other ultrasound platforms to transiently permeabilize the blood-brain barrier (BBB) for drug delivery in neurological disorders and neuro-oncology. Safety trials in humans have followed on from extensive pre-clinical studies, demonstrating a reassuring safety profile and paving the way for numerous translational clinical trials in Alzheimer's disease, Parkinson's disease, and primary and metastatic brain tumors. Future directions include improving ultrasound delivery devices, exploring alternative delivery approaches such as nanodroplets, and expanding the application to other neurological conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.950
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.322
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2024
Admission routes1
Has abstractyes

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